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13 May 2024
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Getting More by Asking for Less: Linking Species Interactions to Species Co-Distributions in Metacommunities

Beyond pairwise species interactions: coarser inference of their joined effects is more relevant

Recommended by ORCID_LOGO based on reviews by Frederik De Laender, Hao Ran Lai and Malyon Bimler

Barbier et al. (2024) investigated the dynamics of species abundances depending on their ecological niche (abiotic component) and on (numerous) competitive interactions. In line with previous evidence and expectations (Barbier et al. 2018), the authors show that it is possible to robustly infer the mean and variance of interaction coefficients from species co-distributions, while it is not possible to infer the individual coefficient values.

The authors devised a simulation framework representing multispecies dynamics in an heterogeneous environmental context (2D grid landscape). They used a Lotka-Volterra framework involving pairwise interaction coefficients and species-specific carrying capacities. These capacities depend on how well the species niche matches the local environmental conditions, through a Gaussian function of the distance of the species niche centers to the local environmental values.

They considered two contrasted scenarios denoted as « Environmental tracking » and « Dispersal limited ». In the latter case, species are initially seeded over the environmental grid and cannot disperse to other cells, while in the former case they can disperse and possibly be more performant in other cells.

The direct effects of species on one another are encoded in an interaction matrix A, and the authors further considered net interactions depending on the inverse of the matrix of direct interactions (Zelnik et al., 2024). The net effects are context-dependent, i.e., it involves the environment-dependent biotic capacities, even through the interaction terms can be defined between species as independent from local environment.

The results presented here underline that the outcome of many individual competitive interactions can only be understood in terms of macroscopic properties. In essence, the results here echoe the mean field theories that investigate the dynamics of average ecological properties instead of the microscopic components (e.g., McKane et al. 2000). In a philosophical perspective, community ecology has long struggled with analyzing and inferring local determinants of species coexistence from species co-occurrence patterns, so that it was claimed that no universal laws can be derived in the discipline (Lawton 1999). Using different and complementary methods and perspectives, recent research has also shown that species assembly parameter values cannot be unambiguously inferred from species co-occurrences only, even in simple designs where an equilibrium can be reached (Poggiato et al. 2021). Although the roles of high-order competitive interactions and intransivity can lead to species coexistence, the simple view of a single loop of competitive interactions is easily challenged when further interactions and complexity is added (Gallien et al. 2024). But should we put so much emphasis on inferring individual interaction coefficients? In a quest to understand the emerging properties of elementary processes, ecological theory could go forward with a more macroscopic analysis and understanding of species coexistence in many communities.

The authors referred several times to an interesting paper from Schaffer (1981), entitled « Ecological abstraction: the consequences of reduced dimensionality in ecological models ». It proposes that estimating individual species competition coefficients is not possible, but that competition can be assessed at the coarser level of organisation, i.e., between ecological guilds. This idea implies that the dimensionality of the competition equations should be greatly reduced to become tractable in practice. Taking together this claim with the results of the present Barbier et al. (2024) paper, it becomes clearer that the nature of competitive interactions can be addressed through « abstracted » quantities, as those of guilds or the moments of the individual competition coefficients (here the average and the standard deviation).

Therefore the scope of Barbier et al. (2024) framework goes beyond statistical issues in parameter inference, but question the way we must think and represent the numerous competitive interactions in a simplified and robust way.

References

Barbier, Matthieu, Jean-François Arnoldi, Guy Bunin, et Michel Loreau. 2018. « Generic assembly patterns in complex ecological communities ». Proceedings of the National Academy of Sciences 115 (9): 2156‑61. https://doi.org/10.1073/pnas.1710352115
 
Barbier, Matthieu, Guy Bunin, et Mathew A Leibold. 2024. « Getting More by Asking for Less: Linking Species Interactions to Species Co-Distributions in Metacommunities ». bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.06.04.543606
 
Gallien, Laure, Maude  Charlie Cavaliere, Marie  Charlotte Grange, François Munoz, et Tamara Münkemüller. 2024. « Intransitive stability collapses under the influence of dominant competitors ». The American Naturalist. https://doi.org/10.1086/730297
 
Lawton, J. H. 1999. « Are There General Laws in Ecology? » Oikos 84 (février):177‑92. https://doi.org/10.2307/3546712
 
McKane, Alan, David Alonso, et Ricard V Solé. 2000. « Mean-field stochastic theory for species-rich assembled communities ». Physical Review E 62 (6): 8466. https://doi.org/10.1103/PhysRevE.62.8466
 
Poggiato, Giovanni, Tamara Münkemüller, Daria Bystrova, Julyan Arbel, James S. Clark, et Wilfried Thuiller. 2021. « On the Interpretations of Joint Modeling in Community Ecology ». Trends in Ecology & Evolution. https://doi.org/10.1016/j.tree.2021.01.002
 
Schaffer, William M. 1981. « Ecological abstraction: the consequences of reduced dimensionality in ecological models ». Ecological monographs 51 (4): 383‑401. https://doi.org/10.2307/2937321
 
Zelnik, Yuval R., Nuria Galiana, Matthieu Barbier, Michel Loreau, Eric Galbraith, et Jean-François Arnoldi. 2024. « How collectively integrated are ecological communities? » Ecology Letters 27 (1): e14358. https://doi.org/10.1111/ele.14358

Getting More by Asking for Less: Linking Species Interactions to Species Co-Distributions in MetacommunitiesMatthieu Barbier, Guy Bunin, Mathew A. Leibold<p>AbstractOne of the more difficult challenges in community ecology is inferring species interactions on the basis of patterns in the spatial distribution of organisms. At its core, the problem is that distributional patterns reflect the ‘realize...Biogeography, Community ecology, Competition, Spatial ecology, Metacommunities & Metapopulations, Species distributions, Statistical ecology, Theoretical ecologyFrançois Munoz2023-10-21 14:14:16 View
25 Oct 2021
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The taxonomic and functional biogeographies of phytoplankton and zooplankton communities across boreal lakes

The difficult interpretation of species co-distribution

Recommended by based on reviews by Anthony Maire and Emilie Macke

Ecology is the study of the distribution of organisms in space and time and their interactions. As such, there is a tradition of studies relating abiotic environmental conditions to species distribution, while another one is concerned by the effects of consumers on the abundance of their resources.  Interestingly, joining the dots appears more difficult than it would suggest: eluding the effect of species interactions on distribution remains one of the greatest challenges to elucidate nowadays (Kissling et al. 2012). Theory suggests that yes, species interactions such as predation and competition should influence range limits (Godsoe et al. 2017), but the common intuition among many biogeographers remains that over large areas such as regions and continents, environmental drivers like temperature and precipitation overwhelm their local effects. Answering this question is of primary importance in the context where species are moving around with climate warming.  Inconsistencies in food web structure may arise with asynchronized movements of consumers and their resources, leading to a major disruption in regulation and potentially ecosystem functioning. Solving this problem, however, remains very challenging because we have to rely on observational data since experiments are hard to perform at the biogeographical scale. 

The study of St-Gelais is an interesting step forward to solve this problem. Their main objective was to assess the strength of the association between phytoplankton and zooplankton communities at a large spatial scale, looking at the spatial covariation of both taxonomic and functional composition. To do so, they undertook a massive survey of more than 100 lakes across three regions of the boreal region of Québec. Species and functional composition were recorded, along with a set of abiotic variables. Classic community ecology at this point. The difficulty they faced was to disentangle the multiple causal relationships involved in the distribution of both trophic levels. Teasing apart bottom-up and top-down forces driving the assembly of plankton communities using observational data is not an easy task. On the one hand, both trophic levels could respond to variations in temperature, nutrient availability and dissolved organic carbon. The interpretation is fairly straightforward if the two levels respond to different factors, but the situation is much more complicated when they do respond similarly. There are potentially three possible underlying scenarios. First, the phyto and zooplankton communities may share the same environmental requirements, thereby generating a joint distribution over gradients such as temperature and nutrient availability. Second, the abiotic environment could drive the distribution of the phytoplankton community, which would then propagate up and influence the distribution of the zooplankton community. Alternatively, the abiotic environment could constrain the distribution of the zooplankton, which could then affect the one of phytoplankton. In addition to all of these factors, St-Gelais et al also consider that dispersal may limit the distribution, well aware of previous studies documenting stronger dispersal limitations for zooplankton communities. 

Unfortunately, there is not a single statistical approach that could be taken from the shelf and used to elucidate drivers of co-distribution. Joint species distribution was once envisioned as a major step forward in this direction (Warton et al. 2015), but there are several limits preventing the direct interpretation that co-occurrence is linked to interactions (Blanchet et al. 2020). Rather, St-Gelais used a variety of multivariate statistics to reveal the structure in their observational data. First, using a Procrustes analysis (a method testing if the spatial variation of one community is correlated to the structure of another community), they found a significant correlation between phytoplankton and zooplankton communities, indicating a taxonomic coupling between the groups. Interestingly, this observation was maintained for functional composition only when interaction-related traits were considered. At this point, these results strongly suggest that interactions are involved in the correlation, but it's hard to decipher between bottom-up and top-down perspectives. A complementary analysis performed with a constrained ordination, per trophic level, provided complementary pieces of information. First observation was that only functional variation was found to be related to the different environmental variables, not taxonomic variation. Despite that trophic levels responded to water quality variables, spatial autocorrelation was more important for zooplankton communities and the two layers appear to respond to different variables. 

It is impossible with those results to formulate a strong conclusion about whether grazing influence the co-distribution of phytoplankton and zooplankton communities. That's the mere nature of observational data. While there is a strong spatial association between them, there are also diverging responses to the different environmental variables considered. But the contrast between taxonomic and functional composition is nonetheless informative and it seems that beyond the idiosyncrasies of species composition, trait distribution may be more informative and general. Perhaps the most original contribution of this study is the hierarchical approach to analyze the data, combined with the simultaneous analysis of taxonomic and functional distributions. Having access to a vast catalog of multivariate statistical techniques, a careful selection of analyses helps revealing key features in the data, rejecting some hypotheses and accepting others. Hopefully, we will see more and more of such multi-trophic approaches to distribution because it is now clear that the factors driving distribution are much more complicated than anticipated in more traditional analyses of community data. Biodiversity is more than a species list, it is also all of the interactions between them, influencing their distribution and abundance (Jordano 2016).

References

Blanchet FG, Cazelles K, Gravel D (2020) Co-occurrence is not evidence of ecological interactions. Ecology Letters, 23, 1050–1063. https://doi.org/10.1111/ele.13525

Godsoe W, Jankowski J, Holt RD, Gravel D (2017) Integrating Biogeography with Contemporary Niche Theory. Trends in Ecology & Evolution, 32, 488–499. https://doi.org/10.1016/j.tree.2017.03.008

Jordano P (2016) Chasing Ecological Interactions. PLOS Biology, 14, e1002559. https://doi.org/10.1371/journal.pbio.1002559

Kissling WD, Dormann CF, Groeneveld J, Hickler T, Kühn I, McInerny GJ, Montoya JM, Römermann C, Schiffers K, Schurr FM, Singer A, Svenning J-C, Zimmermann NE, O’Hara RB (2012) Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents. Journal of Biogeography, 39, 2163–2178. https://doi.org/10.1111/j.1365-2699.2011.02663.x

St-Gelais NF, Vogt RJ, Giorgio PA del, Beisner BE (2021) The taxonomic and functional biogeographies of phytoplankton and zooplankton communities across boreal lakes. bioRxiv, 373332, ver. 4 peer-reviewed and recommended by Peer community in Ecology. https://doi.org/10.1101/373332

Warton DI, Blanchet FG, O’Hara RB, Ovaskainen O, Taskinen S, Walker SC, Hui FKC (2015) So Many Variables: Joint Modeling in Community Ecology. Trends in Ecology & Evolution, 30, 766–779. https://doi.org/10.1016/j.tree.2015.09.007

Wisz MS, Pottier J, Kissling WD, Pellissier L, Lenoir J, Damgaard CF, Dormann CF, Forchhammer MC, Grytnes J-A, Guisan A, Heikkinen RK, Høye TT, Kühn I, Luoto M, Maiorano L, Nilsson M-C, Normand S, Öckinger E, Schmidt NM, Termansen M, Timmermann A, Wardle DA, Aastrup P, Svenning J-C (2013) The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling. Biological Reviews, 88, 15–30. https://doi.org/10.1111/j.1469-185X.2012.00235.x

The taxonomic and functional biogeographies of phytoplankton and zooplankton communities across boreal lakesNicolas F St-Gelais, Richard J Vogt, Paul A del Giorgio, Beatrix E Beisner<p>Strong trophic interactions link primary producers (phytoplankton) and consumers (zooplankton) in lakes. However, the influence of such interactions on the biogeographical distribution of the &nbsp;taxa and functional traits of planktonic organ...Biogeography, Community ecology, Species distributionsDominique Gravel2018-07-24 15:01:51 View
04 Apr 2023
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Data stochasticity and model parametrisation impact the performance of species distribution models: insights from a simulation study

Species Distribution Models: the delicate balance between signal and noise

Recommended by ORCID_LOGO based on reviews by Alejandra Zarzo Arias and 1 anonymous reviewer

Species Distribution Models (SDMs) are one of the most commonly used tools to predict where species are, where they may be in the future, and, at times, what are the variables driving this prediction. As such, applying an SDM to a dataset is akin to making a bet: that the known occurrence data are informative, that the resolution of predictors is adequate vis-à-vis the scale at which their impact is expressed, and that the model will adequately capture the shape of the relationships between predictors and predicted occurrence.

In this contribution, Lambert & Virgili (2023) perform a comprehensive assessment of different sources of complications to this process, using replicated simulations of two synthetic species. Their experimental process is interesting, in that both the data generation and the data analysis stick very close to what would happen in "real life". The use of synthetic species is particularly relevant to the assessment of SDM robustness, as they enable the design of species for which the shape of the relationship is given: in short, we know what the model should capture, and can evaluate the model performance against a ground truth that lacks uncertainty.

Any simulation study is limited by the assumptions established by the investigators; when it comes to spatial data, the "shape" of the landscape, both in terms of auto-correlation and in where the predictors are available. Lambert & Virgili (2023) nicely circumvent these issues by simulating synthetic species against the empirical distribution of predictors; in other words, the species are synthetic, but the environment for which the prediction is made is real. This is an important step forward when compared to the use of e.g. neutral landscapes (With 1997), which can have statistical properties that are not representative of natural landscapes (see e.g. Halley et al., 2004).

A striking point in the study by Lambert & Virgili (2023) is that they reveal a deep, indeed deeper than expected, stochasticity in SDMs; whether this is true in all models remains an open question, but does not invalidate their recommendation to the community: the interpretation of outcomes is a delicate exercise, especially because measures that inform on the goodness of the model fit do not capture the predictive quality of the model outputs. This preprint is both a call to more caution, and a call to more curiosity about the complex behavior of SDMs, while also providing a sensible template to perform future analyses of the potential issues with predictive models.


References

Halley, J. M., et al. (2004) “Uses and Abuses of Fractal Methodology in Ecology: Fractal Methodology in Ecology.” Ecology Letters, vol. 7, no. 3, pp. 254–71. https://doi.org/10.1111/j.1461-0248.2004.00568.x.

Lambert, Charlotte, and Auriane Virgili (2023). Data Stochasticity and Model Parametrisation Impact the Performance of Species Distribution Models: Insights from a Simulation Study. bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.01.17.524386

With, Kimberly A. (1997) “The Application of Neutral Landscape Models in Conservation Biology. Aplicacion de Modelos de Paisaje Neutros En La Biologia de La Conservacion.” Conservation Biology, vol. 11, no. 5, pp. 1069–80. https://doi.org/10.1046/j.1523-1739.1997.96210.x.

Data stochasticity and model parametrisation impact the performance of species distribution models: insights from a simulation studyCharlotte Lambert, Auriane Virgili<p>Species distribution models (SDM) are widely used to describe and explain how species relate to their environment, and predict their spatial distributions. As such, they are the cornerstone of most of spatial planning efforts worldwide. SDM can...Biogeography, Habitat selection, Macroecology, Marine ecology, Spatial ecology, Metacommunities & Metapopulations, Species distributions, Statistical ecologyTimothée Poisot2023-01-20 09:43:51 View
31 Oct 2022
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Ten simple rules for working with high resolution remote sensing data

Preventing misuse of high-resolution remote sensing data

Recommended by ORCID_LOGO based on reviews by Jane Wyngaard and 1 anonymous reviewer

To observe, characterise, identify, understand, predict... This is the approach that researchers follow every day. This sequence is tirelessly repeated as the biological model, the targeted ecosystem and/or the experimental, environmental or modelling conditions change. This way of proceeding is essential in a world of rapid change in response to the frenetic pace of intensifying pressures and forcings that impact ecosystems. To better understand our Earth and the dynamics of its components, to map ecosystems and diversity patterns, and to identify changes, humanity had to demonstrate inventiveness and defy gravity. 

Gustave Hermite and Georges Besançon were the first to launch aloft balloons equipped with radio transmitters, making possible the transmission of meteorological data to observers in real time [1]. The development of aviation in the middle of the 20th century constituted a real leap forward for the frequent acquisition of aerial observations, leading to a significant improvement in weather forecasting models. The need for systematic collection of data as holistic as possible – an essential component for the observation of complex biological systems - has resulted in pushing the limits of technological prowess. 

The conquest of space and the concurrent development of satellite observations has largely contributed to the collection of a considerable mass of data, placing our Earth under the "macroscope" - a concept introduced to ecology in the early 1970s by Howard T. Odum (see [2]), and therefore allowing researchers to move towards a better understanding of ecological systems, deterministic and stochastic patterns … with the ultimate goal of improving management actions [2,3]. Satellite observations have been carried out for nearly five decades now [3] and have greatly contributed to a better qualitative and quantitative understanding of the functioning of our planet, its diversity, its climate... and to a better anticipation of possible future changes (e.g., [4-7]).

This access to rich and complex sources of information, for which both spatial and temporal resolutions are increasingly fine, results in the implementation of increasingly complex computation-based analyses, in order to meet the need for a better understanding of ecological mechanisms and processes, and their possible changes. Steven Levitt stated that "Data is one of the most powerful mechanisms for telling stories". This is so true … Data should not be used as a guide to thinking and a critical judgment at each stage of the data exploitation process should not be neglected. 

This is what Mahood et al. [8] rightly remind us in their article "Ten simple rules for working with high-resolution remote sensing data" in which they provide the fundamentals to consider when working with data of this nature, a still underutilized resource in several topics, such as conservation biology [3]. In this unconventional article, presented in a pedagogical way, the authors remind different generations of readers how satellite data should be handled and processed. The authors aim to make the readers aware of the most frequent pitfalls encouraging them to use data adapted to their original question, the most suitable tools/methods/procedures, to avoid methodological overkill, and to ensure both ethical use of data and transparency in the research process. While access to high-resolution data is increasingly easy thanks to the implementation of dedicated platforms [4], and because of the development of easy-to-use processing software and pipelines, it is important to take the time to recall some of the essential rules and guidelines for managing them, from new users with little or no experience who will find in this article the recommendations, resources and advice necessary to start exploiting remote sensing data, to more experienced researchers.

References

[1] Jeannet P, Philipona R, and Richner H (2016). 8 Swiss upper-air balloon soundings since 1902. In: Willemse S, Furger M (2016) From weather observations to atmospheric and climate sciences in Switzerland: Celebrating 100 years of the Swiss Society for Meteorology. vdf Hochschulverlag AG. 

[2] Odum HT (2007) Environment, Power, and Society for the Twenty-First Century: The Hierarchy of Energy. Columbia University Press.

[3] Boyle SA, Kennedy CM, Torres J, Colman K, Pérez-Estigarribia PE, Sancha NU de la (2014) High-Resolution Satellite Imagery Is an Important yet Underutilized Resource in Conservation Biology. PLOS ONE, 9, e86908. https://doi.org/10.1371/journal.pone.0086908

[4] Le Traon P-Y, Antoine D, Bentamy A, Bonekamp H, Breivik LA, Chapron B, Corlett G, Dibarboure G, DiGiacomo P, Donlon C, Faugère Y, Font J, Girard-Ardhuin F, Gohin F, Johannessen JA, Kamachi M, Lagerloef G, Lambin J, Larnicol G, Le Borgne P, Leuliette E, Lindstrom E, Martin MJ, Maturi E, Miller L, Mingsen L, Morrow R, Reul N, Rio MH, Roquet H, Santoleri R, Wilkin J (2015) Use of satellite observations for operational oceanography: recent achievements and future prospects. Journal of Operational Oceanography, 8, s12–s27. https://doi.org/10.1080/1755876X.2015.1022050

[5] Turner W, Rondinini C, Pettorelli N, Mora B, Leidner AK, Szantoi Z, Buchanan G, Dech S, Dwyer J, Herold M, Koh LP, Leimgruber P, Taubenboeck H, Wegmann M, Wikelski M, Woodcock C (2015) Free and open-access satellite data are key to biodiversity conservation. Biological Conservation, 182, 173–176. https://doi.org/10.1016/j.biocon.2014.11.048

[6] Melet A, Teatini P, Le Cozannet G, Jamet C, Conversi A, Benveniste J, Almar R (2020) Earth Observations for Monitoring Marine Coastal Hazards and Their Drivers. Surveys in Geophysics, 41, 1489–1534. https://doi.org/10.1007/s10712-020-09594-5

[7] Zhao Q, Yu L, Du Z, Peng D, Hao P, Zhang Y, Gong P (2022) An Overview of the Applications of Earth Observation Satellite Data: Impacts and Future Trends. Remote Sensing, 14, 1863. https://doi.org/10.3390/rs14081863

[8] Mahood AL, Joseph MB, Spiers A, Koontz MJ, Ilangakoon N, Solvik K, Quarderer N, McGlinchy J, Scholl V, Denis LS, Nagy C, Braswell A, Rossi MW, Herwehe L, Wasser L, Cattau ME, Iglesias V, Yao F, Leyk S, Balch J (2021) Ten simple rules for working with high resolution remote sensing data. OSFpreprints, ver. 6 peer-reviewed and recommended by Peer Community in Ecology.  https://doi.org/10.31219/osf.io/kehqz

Ten simple rules for working with high resolution remote sensing dataAdam L. Mahood, Maxwell Benjamin Joseph, Anna Spiers, Michael J. Koontz, Nayani Ilangakoon, Kylen Solvik, Nathan Quarderer, Joe McGlinchy, Victoria Scholl, Lise St. Denis, Chelsea Nagy, Anna Braswell, Matthew W. Rossi, Lauren Herwehe, Leah wasser,...<p>Researchers in Earth and environmental science can extract incredible value from high-resolution (sub-meter, sub-hourly or hyper-spectral) remote sensing data, but these data can be difficult to use. Correct, appropriate and competent use of su...Biogeography, Landscape ecology, Macroecology, Spatial ecology, Metacommunities & Metapopulations, Terrestrial ecologyEric Goberville2021-10-19 21:41:22 View
30 Mar 2020
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Environmental variables determining the distribution of an avian parasite: the case of the Philornis torquans complex (Diptera: Muscidae) in South America

Catching the fly in dystopian times

Recommended by based on reviews by 4 anonymous reviewers

Host-parasite interactions are ubiquitous on Earth. They are present in almost every conceivable ecosystem and often result from a long history of antagonist coevolution [1,2]. Recent studies on climate change have revealed, however, that modification of abiotic variables are often accompanied by shifts in the distributional range of parasites to habitats far beyond their original geographical distribution, creating new interactions in novel habitats with unpredictable consequences for host community structure and organization [3,4]. This situation may be especially critical for endangered host species having small population abundance and restricted distribution range. The infestation of bird species with larvae of the muscid fly genus Philornis is a case in point. At least 250 bird species inhabiting mostly Central and South America are infected by Philornis flies [5,6]. Fly larval development occurs in bird faeces, nesting material, or inside nestlings, affecting the development and nestling survival.
Recent reports indicate significant reduction of bird numbers associated with recent Philornis infection, the most conspicuous being Galapagos finches [7,8]. One way to prevent this potential effect consists in to examine the expected geographical shift of Philornis fly species under future climate change scenarios so that anticipatory conservation practices become implemented for endangered bird species. In this regard, Ecological Niche Modeling (ENM) techniques have been increasingly used as a useful tool to predict disease transmission as well as the species becoming infected under different climate change scenarios [9-11]. The paper of Cuervo et al. [12] is an important advance in this regard. By identifying for the first time the macro-environmental variables influencing the abiotic niche of species of the Philornis torquans complex in southern South America, the authors perform a geographical projection model that permits identification of the areas susceptible to be colonized by Philornis species in Argentina, Brazil, and Chile, including habitats where the parasitic fly is still largely absent at present. Their results are promissory for conservation studies and contribute to the still underdeveloped issue of the way climate change impacts on antagonistic ecological relationships.

References

[1] Thompson JN (1994) The Coevolutionary Process. University of Chicago Press.
[2] Poulin R (2007) Evolutionary Ecology of Parasites: (Second Edition). Princeton University Press. doi: 10.2307/j.ctt7sn0x
[3] Pickles RSA, Thornton D, Feldman R, Marques A, Murray DL (2013) Predicting shifts in parasite distribution with climate change: a multitrophic level approach. Global Change Biology, 19, 2645–2654. doi: 10.1111/gcb.12255
[4] Marcogliese DJ (2016) The distribution and abundance of parasites in aquatic ecosystems in a changing climate: More than just temperature. Integrative and Comparative Biology, 56, 611–619. doi: 10.1093/icb/icw036
[5] Dudaniec RY, Kleindorfer S (2006) Effects of the parasitic flies of the genus Philornis (Diptera: Muscidae) on birds. Emu - Austral Ornithology, 106, 13–20. doi: 10.1071/MU04040
[6] Antoniazzi LR, Manzoli DE, Rohrmann D, Saravia MJ, Silvestri L, Beldomenico PM (2011) Climate variability affects the impact of parasitic flies on Argentinean forest birds. Journal of Zoology, 283, 126–134. doi: 10.1111/j.1469-7998.2010.00753.x
[7] Fessl B, Sinclair BJ, Kleindorfer S (2006) The life-cycle of Philornis downsi (Diptera: Muscidae) parasitizing Darwin’s finches and its impacts on nestling survival. Parasitology, 133, 739–747. doi: 10.1017/S0031182006001089
[8] Kleindorfer S, Peters KJ, Custance G, Dudaniec RY, O’Connor JA (2014) Changes in Philornis infestation behavior threaten Darwin’s finch survival. Current Zoology, 60, 542–550. doi: 10.1093/czoolo/60.4.542
[9] Johnson EE, Escobar LE, Zambrana-Torrelio C (2019) An ecological framework for modeling the geography of disease transmission. Trends in Ecology and Evolution, 34, 655–668. doi: 10.1016/j.tree.2019.03.004
[10] Carvalho BM, Rangel EF, Ready PD, Vale MM (2015) Ecological niche modelling predicts southward expansion of Lutzomyia (Nyssomyia) flaviscutellata (Diptera: Psychodidae: Phlebotominae), vector of Leishmania (Leishmania) amazonensis in South America, under climate change. PLOS ONE, 10, e0143282. doi: 10.1371/journal.pone.0143282
[11] Garrido R, Bacigalupo A, Peña-Gómez F, Bustamante RO, Cattan PE, Gorla DE, Botto-Mahan C (2019) Potential impact of climate change on the geographical distribution of two wild vectors of Chagas disease in Chile: Mepraia spinolai and Mepraia gajardoi. Parasites and Vectors, 12, 478. doi: 10.1186/s13071-019-3744-9
[12] Cuervo PF, Percara A, Monje L, Beldomenico PM, Quiroga MA (2020) Environmental variables determining the distribution of an avian parasite: the case of the Philornis torquans complex (Diptera: Muscidae) in South America. bioRxiv, 839589, ver. 5 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/839589

Environmental variables determining the distribution of an avian parasite: the case of the Philornis torquans complex (Diptera: Muscidae) in South AmericaPablo F. Cuervo, Alejandro Percara, Lucas Monje, Pablo M. Beldomenico, Martín A. Quiroga<p>*Philornis* flies are the major cause of myasis in altricial nestlings of neotropical birds. Its impact ranges from subtle to lethal, being of major concern in endangered bird species with geographically-restricted, fragmented and small-sized p...Biogeography, Macroecology, Parasitology, Species distributionsRodrigo Medel2019-11-26 21:31:33 View
12 Jun 2019
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Environmental heterogeneity drives tsetse fly population dynamics and control

Modeling jointly landscape complexity and environmental heterogeneity to envision new strategies for tsetse flies control

Recommended by based on reviews by Timothée Vergne and 1 anonymous reviewer

Today, understanding spatio-temporal dynamics of pathogens is pivotal to understand their transmission and controlling them. First, understanding this dynamics can reveal the ecology of their transmission [1]. Indeed, such knowledge, based on data that are quite easy to access, can shed light on transmission modes, which could rely on different animal species that can be spatially distributed in a non-uniform way [2]. This is especially true for pathogens with complex life-cycles, despite that investigating such dynamics is very challenging and rely mostly on mathematical models.
Moreover, this knowledge can also highlight some weak points in a complex web of transmission and therefore allowing us to envision new innovative control strategies. This has been first proposed on human pathogens, where connectivity among populations can be analyzed to identify which connections need to be targeted to stop or slow down an epidemics [3]. However, this idea is increasingly recognized as a promising new approach for pathogens involving vector populations, especially regarding the complexity to decrease on a long-term the abundance of these vector populations [4].
In "Environmental heterogeneity drives tsetse fly population dynamics and control" [5], Cecilia and co-authors have developed a sophisticated spatio-temporal mechanistic model to figure out how local environment, involved within landscape of different complexities, can impact the population dynamics of tsetse flies, an invertebrate species that can serve as a vector for many pathogens of animal and human importance. They found that spatial patches with the lowest temperature mean and the lowest environmental fluctuations can act as refuge for this species, representing therefore preferential targets for disease control.
The reviewers and I agree that the mathematical framework developed address very well an important topic for both ecological and public health literature. More importantly, it shows how fundamental ecological knowledge can drive pathogen control strategies, opening an interesting avenue for cross-disciplinary research on vector-borne diseases.

References

[1] Grenfell, B. T., Bjørnstad, O. N., & Kappey, J. (2001). Travelling waves and spatial hierarchies in measles epidemics. Nature, 414(6865), 716-723. doi: 10.1038/414716a
[2] Perkins, S. E., Cattadori, I. M., Tagliapietra, V., Rizzoli, A. P., & Hudson, P. J. (2003). Empirical evidence for key hosts in persistence of a tick-borne disease. International journal for parasitology, 33(9), 909-917. doi: 10.1016/S0020-7519(03)00128-0
[3] Colizza, V., Barrat, A., Barthélemy, M., & Vespignani, A. (2006). The role of the airline transportation network in the prediction and predictability of global epidemics. Proceedings of the National Academy of Sciences, 103(7), 2015-2020. doi: 10.1073/pnas.0510525103
[4] Pepin, K. M., Leach, C. B., Marques-Toledo, C., Laass, K. H., Paixao, K. S., et al. (2015) Utility of mosquito surveillance data for spatial prioritization of vector control against dengue viruses in three Brazilian cities. Parasites & Vectors 8, 1–15. doi: 10.1186/s13071-015-0659-y
[5] Cecilia, H., Arnoux, S., Picault, S., Dicko, A., Seck, M. T., Sall, B., Bassène, M., Vreysen, M., Pagabeleguem, S., Bancé, A., Bouyer, J. and Ezanno, P.(2019). Environmental heterogeneity drives tsetse fly population dynamics and control. bioRxiv 493650, ver. 3 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/493650

Environmental heterogeneity drives tsetse fly population dynamics and controlCecilia H, Arnoux S, Picault S, Dicko A, Seck MT, Sall B, Bassene M, Vreysen M, Pagabeleguem S, Bance A, Bouyer J, Ezanno P<p>A spatially and temporally heterogeneous environment may lead to unexpected population dynamics. Knowledge still is needed on which of the local environment properties favour population maintenance at larger scale. For pathogen vectors, such as...Biological control, Population ecology, Spatial ecology, Metacommunities & MetapopulationsBenjamin Roche2018-12-14 12:13:39 View
05 Apr 2022
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Late-acting self-incompatible system, preferential allogamy and delayed selfing in the heterostylous invasive populations of Ludwigia grandiflora subsp. hexapetala

Water primerose (Ludwigia grandiflora subsp. hexapetala) auto- and allogamy: an ecological perspective

Recommended by ORCID_LOGO based on reviews by Juan Arroyo, Emiliano Mora-Carrera and 1 anonymous reviewer

Invasive plant species are widely studied by the ecologist community, especially in wetlands. Indeed, alien plants are considered one of the major threats to wetland biodiversity (Reid et al., 2019). Ludwigia grandiflora subsp. hexapetala (Hook. & Arn.) G.L.Nesom & Kartesz, 2000 (Lgh) is one of them and has received particular attention for a long time (Hieda et al., 2020; Thouvenot, Haury, & Thiebaut, 2013). The ecology of this invasive species and its effect on its biotic and abiotic environment has been studied in previous works. Different processes were demonstrated to explain their invasibility such as allelopathic interference (Dandelot et al., 2008), resource competition (Gérard et al., 2014), and high phenotypic plasticity (Thouvenot, Haury, & Thiébaut, 2013), to cite a few of them. However, although vegetative reproduction is a well-known invasive process for alien plants like Lgh (Glover et al., 2015), the sexual reproduction of this species is still unclear and may help to understand the Lgh population dynamics.

Portillo Lemus et al. (2021) showed that two floral morphs of Lgh co-exist in natura, involving self-compatibility for short-styled phenotype and self-incompatibility for long-styled phenotype processes. This new article (Portillo Lemus et al., 2022) goes further and details the underlying mechanisms of the sexual reproduction of the two floral morphs.

Complementing their previous study, the authors have described a late self-incompatible process associated with the long-styled morph, which authorized a small proportion of autogamy. Although this represents a small fraction of the L-morph reproduction, it may have a considerable impact on the L-morph population dynamics. Indeed, authors report that “floral morphs are mostly found in allopatric monomorphic populations (i.e., exclusively S-morph or exclusively L-morph populations)” with a large proportion of L-morph populations compared to S-morph populations in the field. It may seem counterintuitive as L-morph mainly relies on cross-fecundation. 

Results show that L-morph autogamy mainly occurs in the fall, late in the reproduction season. Therefore, the reproduction may be ensured if no exogenous pollen reaches the stigma of L-morph individuals. It partly explains the large proportion of L-morph populations in the field. 

Beyond the description of late-acting self-incompatibility, which makes the Onagraceae a third family of Myrtales with this reproductive adaptation, the study raises several ecological questions linked to the results presented in the article. First, it seems that even if autogamy is possible, Lgh would favour allogamy, even in S-morph, through the faster development of pollen tubes from other individuals. This may confer an adaptative and evolutive advantage for the Lgh, increasing its invasive potential. The article shows this faster pollen tube development in S-morph but does not test the evolutive consequences. It is an interesting perspective for future research. It would also be interesting to describe cellular processes which recognize and then influence the speed of the pollen tube. Second, the importance of sexual reproduction vs vegetative reproduction would also provide information on the benefits of sexual dimorphism within populations. For instance, how fruit production increases the dispersal potential of Lgh would help to understand Lgh population dynamics and to propose adapted management practices (Delbart et al., 2013; Meisler, 2009).

To conclude, the study proposes a morphological, reproductive and physiological description of the Lgh sexual reproduction process. However, underlying ecological questions are well included in the article and the ecophysiological results enlighten some questions about the role of sexual reproduction in the invasiveness of Lgh. I advise the reader to pay attention to the reviewers’ comments; the debates were very constructive and, thanks to the great collaboration with the authorship, lead to an interesting paper about Lgh reproduction and with promising perspectives in ecology and invasion ecology.

References

Dandelot S, Robles C, Pech N, Cazaubon A, Verlaque R (2008) Allelopathic potential of two invasive alien Ludwigia spp. Aquatic Botany, 88, 311–316. https://doi.org/10.1016/j.aquabot.2007.12.004

Delbart E, Mahy G, Monty A (2013) Efficacité des méthodes de lutte contre le développement de cinq espèces de plantes invasives amphibies : Crassula helmsii, Hydrocotyle ranunculoides, Ludwigia grandiflora, Ludwigia peploides et Myriophyllum aquaticum (synthèse bibliographique). BASE, 17, 87–102. https://popups.uliege.be/1780-4507/index.php?id=9586

Gérard J, Brion N, Triest L (2014) Effect of water column phosphorus reduction on competitive outcome and traits of Ludwigia grandiflora and L. peploides, invasive species in Europe. Aquatic Invasions, 9, 157–166. https://doi.org/10.3391/ai.2014.9.2.04

Glover R, Drenovsky RE, Futrell CJ, Grewell BJ (2015) Clonal integration in Ludwigia hexapetala under different light regimes. Aquatic Botany, 122, 40–46. https://doi.org/10.1016/j.aquabot.2015.01.004

Hieda S, Kaneko Y, Nakagawa M, Noma N (2020) Ludwigia grandiflora (Michx.) Greuter & Burdet subsp. hexapetala (Hook. & Arn.) G. L. Nesom & Kartesz, an Invasive Aquatic Plant in Lake Biwa, the Largest Lake in Japan. Acta Phytotaxonomica et Geobotanica, 71, 65–71. https://doi.org/10.18942/apg.201911

Meisler J (2009) Controlling Ludwigia hexaplata in Northern California. Wetland Science and Practice, 26, 15–19. https://doi.org/10.1672/055.026.0404

Portillo Lemus LO, Harang M, Bozec M, Haury J, Stoeckel S, Barloy D (2022) Late-acting self-incompatible system, preferential allogamy and delayed selfing in the heteromorphic invasive populations of Ludwigia grandiflora subsp. hexapetala. bioRxiv, 2021.07.15.452457, ver. 4 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2021.07.15.452457

Portillo Lemus LO, Bozec M, Harang M, Coudreuse J, Haury J, Stoeckel S, Barloy D (2021) Self-incompatibility limits sexual reproduction rather than environmental conditions in an invasive water primrose. Plant-Environment Interactions, 2, 74–86. https://doi.org/10.1002/pei3.10042

Reid AJ, Carlson AK, Creed IF, Eliason EJ, Gell PA, Johnson PTJ, Kidd KA, MacCormack TJ, Olden JD, Ormerod SJ, Smol JP, Taylor WW, Tockner K, Vermaire JC, Dudgeon D, Cooke SJ (2019) Emerging threats and persistent conservation challenges for freshwater biodiversity. Biological Reviews, 94, 849–873. https://doi.org/10.1111/brv.12480

Thouvenot L, Haury J, Thiebaut G (2013) A success story: water primroses, aquatic plant pests. Aquatic Conservation: Marine and Freshwater Ecosystems, 23, 790–803. https://doi.org/10.1002/aqc.2387

Thouvenot L, Haury J, Thiébaut G (2013) Seasonal plasticity of Ludwigia grandiflora under light and water depth gradients: An outdoor mesocosm experiment. Flora - Morphology, Distribution, Functional Ecology of Plants, 208, 430–437. https://doi.org/10.1016/j.flora.2013.07.004

Late-acting self-incompatible system, preferential allogamy and delayed selfing in the heterostylous invasive populations of Ludwigia grandiflora subsp. hexapetalaLuis O. Portillo Lemus, Maryline Harang, Michel Bozec, Jacques Haury, Solenn Stoeckel, Dominique Barloy<p style="text-align: justify;">Breeding system influences local population genetic structure, effective size, offspring fitness and functional variation. Determining the respective importance of self- and cross-fertilization in hermaphroditic flo...Biological invasions, Botany, Freshwater ecology, PollinationAntoine Vernay2021-07-16 09:53:50 View
16 Jun 2023
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Colonisation debt: when invasion history impacts current range expansion

Combining stochastic models and experiments to understand dispersal in heterogeneous environments

Recommended by based on reviews by 2 anonymous reviewers

Dispersal is a key element of the natural dynamics of meta-communities, and plays a central role in the success of populations colonizing new landscapes. Understanding how demographic processes may affect the speed at which alien species spread through environmentally-heterogeneous habitat fragments is therefore of key importance to manage biological invasions. This requires studying together the complex interplay of dispersal and population processes, two inextricably related phenomena that can produce many possible outcomes. Stochastic models offer an opportunity to describe this kind of process in a meaningful way, but to ensure that they are realistic (sensu Levins 1966) it is also necessary to combine model simulations with empirical data (Snäll et al. 2007).

Morel-Journel et al. (2023) put together stochastic models and experimental data to study how population density may affect the speed at which alien species spread through a heterogeneous landscape. They do it by focusing on what they call ‘colonisation debt’, which is merely the impact that population density at the invasion front may have on the speed at which the species colonizes patches of different carrying capacities. They investigate this issue through two largely independent approaches. First, a stochastic model of dispersal throughout the patches of a linear, 1-dimensional landscape, which accounts for different degrees of density-dependent growth. And second, a microcosm experiment of a parasitoid wasp colonizing patches with different numbers of host eggs. In both cases, they compare the velocity of colonization of patches with lower or higher carrying capacity than the previous one (i.e. what they call upward or downward gradients).

Their results show that density-dependent processes influence the speed at which new fragments are colonized is significantly reduced by positive density dependence. When either population growth or dispersal rate depend on density, colonisation debt limits the speed of invasion, which turns out to be dependent on the strength and direction of the gradient between the conditions of the invasion front, and the newly colonized patches. Although this result may be quite important to understand the meta-population dynamics of dispersing species, it is important to note that in their study the environmental differences between patches do not take into account eventual shifts in the scenopoetic conditions (i.e. the values of the environmental parameters to which species niches’ respond to; Hutchinson 1978, see also Soberón 2007). Rather, differences arise from variations in the carrying capacity of the patches that are consecutively invaded, both in the in silico and microcosm experiments. That is, they account for potential differences in the size or quality of the invaded fragments, but not on the costs of colonizing fragments with different environmental conditions, which may also determine invasion speed through niche-driven processes. This aspect can be of particular importance in biological invasions or under climate change-driven range shifts, when adaptation to new environments is often required (Sakai et al. 2001; Whitney & Gabler 2008; Hill et al. 2011).

The expansion of geographical distribution ranges is the result of complex eco-evolutionary processes where meta-community dynamics and niche shifts interact in a novel physical space and/or environment (see, e.g., Mestre et al. 2020). Here, the invasibility of native communities is determined by niche variations and how similar are the traits of alien and native species (Hui et al. 2023). Within this context, density-dependent processes will build upon and heterogeneous matrix of native communities and environments (Tischendorf et al. 2005), to eventually determine invasion success. What the results of Morel-Journel et al. (2023) show is that, when the invader shows density dependence, the invasion process can be slowed down by variations in the carrying capacity of patches along the dispersal front. This can be particularly useful to manage biological invasions; ongoing invasions can be at least partially controlled by manipulating the size or quality of the patches that are most adequate to the invader, controlling host populations to reduce carrying capacity. But further, landscape manipulation of such kind could be used in a preventive way, to account in advance for the effects of the introduction of alien species for agricultural exploitation or biological control, thereby providing an additional safeguard to practices such as the introduction of parasitoids to control plagues. These practical aspects are certainly worth exploring further, together with a more explicit account of the influence of the abiotic conditions and the characteristics of the invaded communities on the success and speed of biological invasions.

REFERENCES

Hill, J.K., Griffiths, H.M. & Thomas, C.D. (2011) Climate change and evolutionary adaptations at species' range margins. Annual Review of Entomology, 56, 143-159. https://doi.org/10.1146/annurev-ento-120709-144746

Hui, C., Pyšek, P. & Richardson, D.M. (2023) Disentangling the relationships among abundance, invasiveness and invasibility in trait space. npj Biodiversity, 2, 13. https://doi.org/10.1038/s44185-023-00019-1

Hutchinson, G.E. (1978) An introduction to population biology. Yale University Press, New Haven, CT.

Levins, R. (1966) The strategy of model building in population biology. American Scientist, 54, 421-431. 

Mestre, A., Poulin, R. & Hortal, J. (2020) A niche perspective on the range expansion of symbionts. Biological Reviews, 95, 491-516. https://doi.org/10.1111/brv.12574

Morel-Journel, T., Haond, M., Duan, L., Mailleret, L. & Vercken, E. (2023) Colonisation debt: when invasion history impacts current range expansion. bioRxiv, 2022.11.13.516255, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.11.13.516255

Snäll, T., B. O'Hara, R. & Arjas, E. (2007) A mathematical and statistical framework for modelling dispersal. Oikos, 116, 1037-1050. https://doi.org/10.1111/j.0030-1299.2007.15604.x

Sakai, A.K., Allendorf, F.W., Holt, J.S., Lodge, D.M., Molofsky, J., With, K.A., Baughman, S., Cabin, R.J., Cohen, J.E., Ellstrand, N.C., McCauley, D.E., O'Neil, P., Parker, I.M., Thompson, J.N. & Weller, S.G. (2001) The population biology of invasive species. Annual Review of Ecology and Systematics, 32, 305-332. https://doi.org/10.1146/annurev.ecolsys.32.081501.114037

Soberón, J. (2007) Grinnellian and Eltonian niches and geographic distributions of species. Ecology Letters, 10, 1115-1123. https://doi.org/10.1111/j.1461-0248.2007.01107.x

Tischendorf, L., Grez, A., Zaviezo, T. & Fahrig, L. (2005) Mechanisms affecting population density in fragmented habitat. Ecology and Society, 10, 7. https://doi.org/10.5751/ES-01265-100107

Whitney, K.D. & Gabler, C.A. (2008) Rapid evolution in introduced species, 'invasive traits' and recipient communities: challenges for predicting invasive potential. Diversity and Distributions, 14, 569-580. https://doi.org/10.1111/j.1472-4642.2008.00473.x

Colonisation debt: when invasion history impacts current range expansionThibaut Morel-Journel, Marjorie Haond, Lana Duan, Ludovic Mailleret, Elodie Vercken<p>Demographic processes that occur at the local level, such as positive density dependence in growth or dispersal, are known to shape population range expansion, notably by linking carrying capacity to invasion speed. As a result of these process...Biological invasions, Colonization, Dispersal & Migration, Experimental ecology, Landscape ecology, Population ecology, Spatial ecology, Metacommunities & Metapopulations, Theoretical ecologyJoaquín HortalAnonymous, Anonymous2022-11-16 15:52:08 View
20 Sep 2018
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When higher carrying capacities lead to faster propagation

When the dispersal of the many outruns the dispersal of the few

Recommended by ORCID_LOGO based on reviews by Yuval Zelnik and 1 anonymous reviewer

Are biological invasions driven by a few pioneers, running ahead of their conspecifics? Or are these pioneers constantly being caught up by, and folded into, the larger flux of propagules from the established populations behind them?
In ecology and beyond, these two scenarios are known as "pulled" and "pushed" fronts, and they come with different expectations. In a pushed front, invasion speed is not just a matter of how good individuals are at dispersing and settling new locations. It becomes a collective, density-dependent property of population fluxes. And in particular, it can depend on the equilibrium abundance of the established populations inside the range, i.e. the species’ carrying capacity K, factoring in its abiotic environment and biotic interactions.
This realization is especially important because it can flip around our expectations about which species expand fast, and how to manage them. We tend to think of initial colonization and long-term abundance as two independent axes of variation among species or indeed as two ends of a spectrum, in the classic competition-colonization tradeoff [1]. When both play into invasion speed, good dispersers might not outrun good competitors. This is useful knowledge, whether we want to contain an invasion or secure a reintroduction.
In their study "When higher carrying capacities lead to faster propagation", Haond et al [2] combine mathematical analysis, Individual-Based simulations and experiments to show that various mechanisms can cause pushed fronts, whose speed increases with the carrying capacity K of the species. Rather than focus on one particular angle, the authors endeavor to demonstrate that this qualitative effect appears again and again in a variety of settings.
It is perhaps surprising that this notable and general connection between K and invasion speed has managed to garner so little fame in ecology. A large fraction of the literature employs the venerable Fisher-KPP reaction-diffusion model, which combines local logistic growth with linear diffusion in space. This model has prompted both considerable mathematical developments [3] and many applications to modelling real invasions [4]. But it only allows pulled fronts, driven by the small populations at the edge of a species range, with a speed that depends only on their initial growth rate r.
This classic setup is, however, singular in many ways. Haond et al [2] use it as a null model, and introduce three mechanisms or factors that each ensure a role of K in invasion speed, while giving less importance to the pioneers at the border.
Two factors, the Allee effect and demographic stochasticity, make small edge populations slower to grow or less likely to survive. These two factors are studied theoretically, and to make their claims stronger, the authors stack the deck against K. When generalizing equations or simulations beyond the null case, it is easy to obtain functional forms where the parameter K does not only play the role of equilibrium carrying capacity, but also affects dynamical properties such as the maximum or mean growth rate. In that case, it can trivially change the propagation speed, without it meaning anything about the role of established populations behind the front. Haond et al [2] avoid this pitfall by disentangling these effects, at the cost of slightly more peculiar expressions, and show that varying essentially nothing but the carrying capacity can still impact the speed of the invasion front.
The third factor, density-dependent dispersal, makes small populations less prone to disperse. It is well established empirically and theoretically that various biological mechanisms, from collective organization to behavioral switches, can prompt organisms in denser populations to disperse more, e.g. in such a way as to escape competition [5]. The authors demonstrate how this effect induces a link between carrying capacity and invasion speed, both theoretically and in a dispersal experiment on the parasitoid wasp, Trichogramma chilonis.
Overall, this study carries a simple and clear message, supported by valuable contributions from different angles. Although some sections are clearly written for the theoretical ecology crowd, this article has something for everyone, from the stray physicist to the open-minded manager. The collaboration between theoreticians and experimentalists, while not central, is worthy of note. Because the narrative of this study is the variety of mechanisms that can lead to the same qualitative effect, the inclusion of various approaches is not a gimmick, but helps drive home its main message. The work is fairly self-contained, although one could always wish for further developments, especially in the direction of more quantitative testing of these mechanisms.
In conclusion, Haond et al [2] effectively convey the widely relevant message that, for some species, invading is not just about the destination, it is about the many offspring one makes along the way.

References

[1] Levins, R., & Culver, D. (1971). Regional Coexistence of Species and Competition between Rare Species. Proceedings of the National Academy of Sciences, 68(6), 1246–1248. doi: 10.1073/pnas.68.6.1246
[2] Haond, M., Morel-Journel, T., Lombaert, E., Vercken, E., Mailleret, L., & Roques, L. (2018). When higher carrying capacities lead to faster propagation. BioRxiv, 307322. doi: 10.1101/307322
[3] Crooks, E. C. M., Dancer, E. N., Hilhorst, D., Mimura, M., & Ninomiya, H. (2004). Spatial segregation limit of a competition-diffusion system with Dirichlet boundary conditions. Nonlinear Analysis: Real World Applications, 5(4), 645–665. doi: 10.1016/j.nonrwa.2004.01.004
[4] Shigesada, N., & Kawasaki, K. (1997). Biological Invasions: Theory and Practice. Oxford University Press, UK.
[5] Matthysen, E. (2005). Density-dependent dispersal in birds and mammals. Ecography, 28(3), 403–416. doi: 10.1111/j.0906-7590.2005.04073.x

When higher carrying capacities lead to faster propagationMarjorie Haond, Thibaut Morel-Journel, Eric Lombaert, Elodie Vercken, Ludovic Mailleret & Lionel Roques<p>This preprint has been reviewed and recommended by Peer Community In Ecology (https://dx.doi.org/10.24072/pci.ecology.100004). Finding general patterns in the expansion of natural populations is a major challenge in ecology and invasion biology...Biological invasions, Colonization, Dispersal & Migration, Experimental ecology, Population ecology, Spatial ecology, Metacommunities & Metapopulations, Theoretical ecologyMatthieu Barbier Yuval Zelnik2018-04-25 10:18:48 View
20 Feb 2019
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Differential immune gene expression associated with contemporary range expansion of two invasive rodents in Senegal

Are all the roads leading to Rome?

Recommended by based on reviews by Nadia Aubin-Horth and 1 anonymous reviewer

Identifying the factors which favour the establishment and spread of non-native species in novel environments is one of the keys to predict - and hence prevent or control - biological invasions. This includes biological factors (i.e. factors associated with the invasive species themselves), and one of the prevailing hypotheses is that some species traits may explain their impressive success to establish and spread in novel environments [1]. In animals, most research studies have focused on traits associated with fecundity, age at maturity, level of affiliation to humans or dispersal ability for instance. The “composite picture” of the perfect (i.e. successful) invader that has gradually emerged is a small-bodied animal strongly affiliated to human activities with high fecundity, high dispersal ability and a super high level of plasticity. Of course, the story is not that simple, and actually a perfect invader sometimes – if not often- takes another form… Carrying on to identify what makes a species a successful invader or not is hence still an important research axis with major implications.
In this manuscript, Charbonnel and collaborators [2] provide an interesting opportunity to gain novel insights into our understanding of (the) traits underlying invasion success. They nicely combine the power of Next-Generation Sequencing (NGS) with a clever comparative approach of two closely-related invasive rodents (the house mouse Mus musculus and the black rat Rattus rattus) in a common environment. They use this experimental design to test the appealing hypothesis that pathogens may be actors of the story, and may indirectly explain why some non-native species are so successful in invading novel habitats.
It is generally assumed that the community of pathogens encountered by non-native species in novel environments is different from that of their native area. On the one hand (the enemy-release hypothesis), it can be hypothesized that non-native species, when they arrive into a novel environment, will be relaxed from the pressure imposed by their native pathogens because local pathogens are not adapted (and hence do not infect) to this novel host. Because immune defence against pathogens is highly costly, non-native species establishing into a novel environment could hence reallocate these costs to other functions such as fecundity or dispersal apparatus. This scenario has been termed the “evolution of increased competitive ability” (EICA) hypothesis [3]. On the other hand (the EICA-refined hypothesis [4]), one can assume that invaders will encounter new pathogens in newly established areas, and will allocate energy toward cost-effective immune pathways to permit allocating a non-negligible amount of energy toward other functions. Finally, a last hypothesis (the “immune protection” hypothesis) assumes major changes in pathogen composition between native and invaded areas, which should lead to an overall increase in immune investment by the native species to successfully invade novel environments [4]. This last hypothesis suggests that only non-native species being able to take up the associated costs of immunity will be successful invaders.
The role of immunity in invasion success has yet been poorly investigated, mainly because of the difficulty to simultaneously analyse multiple immune pathways [4]. Charbonnel and collaborators [2] overpass this difficulty by screening all genes expressed (using a whole RNA sequencing approach) in an immune tissue: the spleen. They do so along the invasion routes of two sympatric invasive rodents in Africa and compare anciently and newly invaded areas (respectively). For one of the two species (the house mouse), they found a high number of immune-related genes to be up-regulated in newly invaded areas compared to anciently invaded areas. All categories of immune pathways (costly and cost-effective) were up-regulated, suggesting an overall increase in immune investment in the mouse, which corroborates the “immune protection” hypothesis. For the black rat, patterns of gene expression were somewhat different, with much less pronounced differentiation in gene expression between newly and anciently invaded areas. Among the few differentiated genes, a few were associated to immune responses and some of theses genes were even down-regulated in the newly invaded areas. This pattern may actually corroborate the EICA hypothesis, although it could alternatively suggest that stochastic processes (drift) associated to recent decrease in population size (which is expected during a colonisation event) are more important than selection imposed by pathogens in shaping patterns of immune gene expression.
Overall, this study [2] suggests (i) that immune-related traits are important in predicting invasion success and (ii) that two successful species with a similar invasion history and living in similar environments can use different life-history strategies to reach the same success. This later finding is particularly relevant and intriguing as it suggests that the traits and strategies deployed by species to colonise new habitats might actually be idiosyncratic, and that, if general trends actually emerge in regards of traits predicting the success of invaders, the devil might actually be into the details. Comparative studies are extremely important to identify the general rules and the specificities sustaining actual patterns, but these approaches are yet poorly used in biological invasions (at least empirically). The work presented by Charbonnel and colleagues [2] calls for future comparative studies performed at multiple spatial scales (native vs. non-native areas, anciently vs. recently invaded areas), multiple taxonomic resolutions and across multiple traits (to search for trade-offs), so that the success of invasive species can be properly understood and predicted.

References

[1] Jeschke, J. M., & Strayer, D. L. (2006). Determinants of vertebrate invasion success in Europe and North America. Global Change Biology, 12(9), 1608-1619. doi: 10.1111/j.1365-2486.2006.01213.x
[2] Blossey, B., & Notzold, R. (1995). Evolution of increased competitive ability in invasive nonindigenous plants: a hypothesis. Journal of Ecology, 83(5), 887-889. doi: 10.2307/2261425
[3] Charbonnel, N., Galan, M., Tatard, C., Loiseau, A., Diagne, C. A., Dalecky, A., Parrinello, H., Rialle, S., Severac, D., & Brouat, C. (2019). Differential immune gene expression associated with contemporary range expansion of two invasive rodents in Senegal. bioRxiv, 442160, ver. 5 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/442160
[4] Lee, K. A., & Klasing, K. C. (2004). A role for immunology in invasion biology. Trends in Ecology & Evolution, 19(10), 523-529. doi: 10.1016/j.tree.2004.07.012

Differential immune gene expression associated with contemporary range expansion of two invasive rodents in SenegalNathalie Charbonnel, Maxime Galan, Caroline Tatard, Anne Loiseau, Christophe Diagne, Ambroise Dalecky, Hugues Parrinello, Stephanie Rialle, Dany Severac and Carine Brouat<p>Background: Biological invasions are major anthropogenic changes associated with threats to biodiversity and health. What determines the successful establishment of introduced populations still remains unsolved. Here we explore the appealing as...Biological invasions, Eco-immunology & Immunity, Population ecologySimon Blanchet2018-10-14 12:21:52 View